Multidimensional Data Visualization

This collection of essays brings together many of the world's most distinguished statisticians to discuss a wide array of the most important recent developments in data analysis. The book honors John

Insurers: use analytics to drive far more value from your most important asset -- data! Today, many insurers radically underutilize their data, leaving them vulnerable to traditional and non-tradition

A practical guide to leveraging your data to spur innovation and growth Your business generates reams of data, but what do you do with it? Reporting is only the beginning. Your data holds the key to

This book explores the EU Dicode project, which facilitates collaboration and decision making in data-intensive and cognitively complex settings. The emphasis is on exploitation of big data, and on co

Get Ahead Medicine: OSCEs and Data Interpretation, the latest addition to the essential Get ahead! revision series, provides practical and invaluable revision for all medical students preparing for th

Reference questions seeking the raw data that lies behind statistics is a service that has been mostly handled by academic research libraries. Yet with the growth of the Internet and the rise of relat

This is a new edition of a highly praised, successful reference on data mining, now more important than ever due to the growth of the field and wide range of applications. This edition features new ch

Massive amounts of data on human beings can now be analyzed. Pragmatic purposes abound, including selling goods and services, winning political campaigns, and identifying possible terrorists. Yet 'big data' can also be harnessed to serve the public good: scientists can use big data to do research that improves the lives of human beings, improves government services, and reduces taxpayer costs. In order to achieve this goal, researchers must have access to this data - raising important privacy questions. What are the ethical and legal requirements? What are the rules of engagement? What are the best ways to provide access while also protecting confidentiality? Are there reasonable mechanisms to compensate citizens for privacy loss? The goal of this book is to answer some of these questions. The book's authors paint an intellectual landscape that includes legal, economic, and statistical frameworks. The authors also identify new practical approaches that simultaneously maximize the utili

Massive amounts of data on human beings can now be analyzed. Pragmatic purposes abound, including selling goods and services, winning political campaigns, and identifying possible terrorists. Yet 'big data' can also be harnessed to serve the public good: scientists can use big data to do research that improves the lives of human beings, improves government services, and reduces taxpayer costs. In order to achieve this goal, researchers must have access to this data - raising important privacy questions. What are the ethical and legal requirements? What are the rules of engagement? What are the best ways to provide access while also protecting confidentiality? Are there reasonable mechanisms to compensate citizens for privacy loss? The goal of this book is to answer some of these questions. The book's authors paint an intellectual landscape that includes legal, economic, and statistical frameworks. The authors also identify new practical approaches that simultaneously maximize the utili

This entry-level text offers clear and concise guidelines on how to select, construct, interpret, and evaluate count data. Written for researchers with little or no background in advanced statistics, the book presents treatments of all major models using numerous tables, insets, and detailed modeling suggestions. It begins by demonstrating the fundamentals of modeling count data, including a thorough presentation of the Poisson model. It then works up to an analysis of the problem of overdispersion and of the negative binomial model, and finally to the many variations that can be made to the base count models. Examples in Stata, R, and SAS code enable readers to adapt models for their own purposes, making the text an ideal resource for researchers working in health, ecology, econometrics, transportation, and other fields.

This entry-level text offers clear and concise guidelines on how to select, construct, interpret, and evaluate count data. Written for researchers with little or no background in advanced statistics, the book presents treatments of all major models using numerous tables, insets, and detailed modeling suggestions. It begins by demonstrating the fundamentals of modeling count data, including a thorough presentation of the Poisson model. It then works up to an analysis of the problem of overdispersion and of the negative binomial model, and finally to the many variations that can be made to the base count models. Examples in Stata, R, and SAS code enable readers to adapt models for their own purposes, making the text an ideal resource for researchers working in health, ecology, econometrics, transportation, and other fields.

Between tweets, likes, comments, blogs, videos and images, today’s customer is estimated to generate 2.5 quintillion bytes of data per day. How can marketers utilize the ever-increasing amount of data

One of the grand challenges in our digital world are the large, complex and often weakly structured data sets, and massive amounts of unstructured information. This “big data” challenge is most eviden

In this comprehensive guide to using data to plan differentiated instruction, the authors present step-by-step techniques and planning tools to help teachers design learning that allows all students t

A modern and practical guide to the essential concepts and ideas for analyzing data with missing observations in the field of biostatisticsWith an emphasis on hands-on applications, Applied Missing Da

Addressing recent challenges and developments in this growing field, Multisensor Data Fusion Uncertainty Theory first discusses basic questions such as: Why and when is multiple sensor fusion necessar

Learn the value of conceptual, logical, and physical data modeling and how each stage increases our knowledge of the data and reduces assumptions and poor design decisions in MongoDB.

The Little Green Data Book is a pocket-sized ready reference on key environmental data for over 200 countries. Key indicators are organized under the headings of agriculture, forestry, biodiversity, o

"This book provides a central source of reference on the various data management techniques of large scale data processing and its technology application. This book presents chapters written by leadin

Written for students and researchers in statistics and biostatistics, this book presents a modern introduction to categorical data analysis, with R integrated into the text as a data analysis method a

Rather than the broad array of topics in most textbooks on business databases, Umanath and Scamell focus on data modeling and database design to provide a robust understanding of these core areas. Thi

Leading and managing change in schools is a complex topic. In this timely book the authors take the reader through a journey of how to lead and manage multidimensional change in order to create engage

This book provides a comprehensive overview of calibration and validation techniques for traffic simulation models. It details the data required as an input for the calibration and validation processe

In four studies written during the first and second decades of the century, Csatar considers some of the basic questions of methodology and data structure in the cognitive research of metaphor. They c

What are the most effective methods to code and analyze data for a particular study? This thoughtful and engaging book reviews the selection criteria for coding and analyzing any set of data--whether

The book presents state-of-the-art works in computational engineering. Focus is on mathematical modeling, numerical simulation, experimental validation and visualization in engineering sciences. In pa

What are the most effective methods to code and analyze data for a particular study? This thoughtful and engaging book reviews the selection criteria for coding and analyzing any set of data--whether

Traditional Database Management Systems are built on the concept of persistent data sets, that are stored reliably in stable storage and queried/updated several times throughout their lifetime. For se

This revised and updated edition focuses on constrained ordination (RDA, CCA), variation partitioning and the use of permutation tests of statistical hypotheses about multivariate data. Both classification and modern regression methods (GLM, GAM, loess) are reviewed and species functional traits and spatial structures analysed. Nine case studies of varying difficulty help to illustrate the suggested analytical methods, using the latest version of Canoco 5. All studies utilise descriptive and manipulative approaches, and are supported by data sets and project files available from the book website: http://regent.prf.jcu.cz/maed2/. Written primarily for community ecologists needing to analyse data resulting from field observations and experiments, this book is a valuable resource to students and researchers dealing with both simple and complex ecological problems, such as the variation of biotic communities with environmental conditions or their response to experimental manipulation.

"This book highlights contemporary findings in the area of biologically-inspired techniques in data mining domains and their implementation in real-life problems"--

"This book explores current research in data mining, including the important trends and patterns and their impact in fields such as software engineering, and focuses on modern techniques as well as pa

Describes the sciences of cloud computing and large data sets, providing critical analysis and context while asking questions about who controls these systems and what the consequences are.

Describes the sciences of cloud computing and large data sets, providing critical analysis and context while asking questions about who controls these systems and what the consequences are.

This Little Data Book presents tables for over 213 economies showing the most recent national data on key indicators of information and communications technology (ICT), including access, quality, affo

"This book presents a comprehensive treatment of ground penetrating radar using both forward and inverse scattering mathematical techniques. Use of field data instead of laboratory data enables reader

Variational Regularization of 3D Data provides an introduction to variational methods for data modelling and its application in computer vision. In this book, the authors identify interpolation as an

Strong data management knowledge and skills are a requirement for every DNP graduate. This unique text focuses on fostering the rigorous, meticulous data management skills that can improve care experi

The crisis of global capitalism that has unfolded since 2008 is more than an economic crisis. It is structural and multidimensional. The sequence of events that have taken place in its aftermath show

This SpringerBrief presents the concept of the smart grid architecture and investigates the security issues of the smart grid and the existing encrypted data query techniques. Unique characteristics o

An expert guide to high performance computing architectures and how they relate to analytics and data miningWith the exponential growth of data comes an ever-increasing need to process and analyze so-